会员体验
专利管家(专利管理)
工作空间(专利管理)
风险监控(情报监控)
数据分析(专利分析)
侵权分析(诉讼无效)
联系我们
交流群
官方交流:
QQ群: 891211   
微信请扫码    >>>
现在联系顾问~
热词
    • 5. 发明授权
    • Biomarker evaluation through image analysis
    • 通过图像分析进行生物标记评估
    • US09042630B2
    • 2015-05-26
    • US13282450
    • 2011-10-26
    • Gerd BinnigMaria AthelogouGuenter Schmidt
    • Gerd BinnigMaria AthelogouGuenter Schmidt
    • G06K9/00G06T7/00
    • G06T7/0012G06K9/0014G06K9/34G06K9/4652G06K9/6215G06T7/11G06T7/155G06T7/187G06T7/90G06T2207/10024G06T2207/10056G06T2207/30024
    • A method for determining whether a test biomarker is a stain for a type of cell component, such as membrane or nucleus, involves performing various segmentation processes on an image of tissue stained with the test biomarker. One segmentation process searches for a first cell component type, and another segmentation process searches for a second cell component type by segmenting only stained pixels. The test biomarker is identified as a stain for each component type if the process identifies the component based only on stained pixels. Whether the test biomarker is a membrane stain or nucleus stain is displayed on a graphical user interface. In addition, the method identifies stained pixels corresponding to a second cell component using pixels determined to correspond to a first cell component. An expression profile for the test biomarker is then displayed that indicates the proportion of stained pixels in each type of cell component.
    • 用于确定测试生物标志物是否是细胞成分(例如膜或细胞核)类型的污渍的方法包括对用测试生物标志物染色的组织的图像执行各种分割过程。 一个分割过程搜索第一个单元分量类型,另一个分割过程通过仅分割染色的像素来搜索第二单元分量类型。 如果过程仅基于染色的像素识别组分,则将测试生物标志物鉴定为每种组分类型的污点。 测试生物标志物是膜污点还是核染色体显示在图形用户界面上。 此外,该方法使用被确定为对应于第一单元组件的像素来识别与第二单元组件对应的染色像素。 然后显示用于测试生物标志物的表达谱,其指示每种类型细胞组分中染色像素的比例。
    • 6. 发明申请
    • Automatic image analysis and quantification for fluorescence in situ hybridization
    • 荧光原位杂交的自动图像分析和定量
    • US20080137937A1
    • 2008-06-12
    • US11607557
    • 2006-11-30
    • Maria AthelogouGerd BinnigGuenter SchmidtTamara ManuelianJoachim Diebold
    • Maria AthelogouGerd BinnigGuenter SchmidtTamara ManuelianJoachim Diebold
    • G06K9/00
    • G06T7/0012G06K9/0014G06T7/90G06T2207/30024
    • An analysis system automatically analyzes and counts fluorescence signals present in biopsy tissue marked using Fluorescence in situ Hybridization (FISH). The user of the system specifies classes of a class network and process steps of a process hierarchy. Then pixel values in image slices of biopsy tissue are acquired in three dimensions. A computer-implemented network structure is generated by linking pixel values to objects of a data network according to the class network and process hierarchy. Objects associated with pixel values at different depths of the biopsy tissue are used to determine the number, volume and distance between cell components. In one application, fluorescence signals that mark Her2/neural genes and centromeres of chromosome seventeen are counted to diagnose breast cancer. Her2/neural genes that overlap one another or that are covered by centromeres can be accurately counted. Signal artifacts that do not mark genes can be identified by their excessive volume.
    • 分析系统自动分析和计数使用荧光原位杂交(FISH)标记的活检组织中存在的荧光信号。 系统的用户指定类网络的类和进程层次结构的处理步骤。 然后在三维中获取活检组织的图像切片中的像素值。 通过根据类网络和进程层次将像素值链接到数据网络的对象来生成计算机实现的网络结构。 与活检组织不同深度处的像素值相关联的物体用于确定细胞组分之间的数量,体积和距离。 在一个应用中,计数标记Her2 /神经基因的荧光信号和17号染色​​体的着丝粒被诊断为乳腺癌。 可以准确计算Her2 /彼此重叠或被着丝粒覆盖的神经基因。 不标记基因的信号伪影可以通过其过量的体积来识别。
    • 8. 发明申请
    • Automatic image analysis and quantification for fluorescence in situ hybridization
    • 荧光原位杂交的自动图像分析和定量
    • US20120237106A1
    • 2012-09-20
    • US13199412
    • 2011-08-29
    • Maria AthelogouGerd BinnigGuenter SchmidtTamara ManuelianJoachim Diebold
    • Maria AthelogouGerd BinnigGuenter SchmidtTamara ManuelianJoachim Diebold
    • G06K9/00
    • G06T7/0012G06K9/0014G06T7/90G06T2207/30024
    • An analysis system automatically analyzes and counts fluorescence signals present in biopsy tissue marked using Fluorescence in situ Hybridization (FISH). The user of the system specifies classes of a class network and process steps of a process hierarchy. Then pixel values in image slices of biopsy tissue are acquired in three dimensions. A computer-implemented network structure is generated by linking pixel values to objects of a data network according to the class network and process hierarchy. Objects associated with pixel values at different depths of the biopsy tissue are used to determine the number, volume and distance between cell components. In one application, fluorescence signals that mark Her2/neural genes and centromeres of chromosome seventeen are counted to diagnose breast cancer. Her2/neural genes that overlap one another or that are covered by centromeres can be accurately counted. Signal artifacts that do not mark genes can be identified by their excessive volume.
    • 分析系统自动分析和计数使用荧光原位杂交(FISH)标记的活检组织中存在的荧光信号。 系统的用户指定类网络的类和进程层次结构的处理步骤。 然后在三维中获取活检组织的图像切片中的像素值。 通过根据类网络和进程层次将像素值链接到数据网络的对象来生成计算机实现的网络结构。 与活检组织不同深度处的像素值相关联的物体用于确定细胞组分之间的数量,体积和距离。 在一个应用中,计数标记Her2 /神经基因的荧光信号和17号染色​​体的着丝粒被诊断为乳腺癌。 可以准确计算Her2 /彼此重叠或被着丝粒覆盖的神经基因。 不标记基因的信号伪影可以通过其过量的体积来识别。
    • 10. 发明授权
    • Automatic image analysis and quantification for fluorescence in situ hybridization
    • 荧光原位杂交的自动图像分析和定量
    • US08019134B2
    • 2011-09-13
    • US11607557
    • 2006-11-30
    • Maria AthelogouGerd BinnigGuenter SchmidtTamara ManuelianJoachim Diebold
    • Maria AthelogouGerd BinnigGuenter SchmidtTamara ManuelianJoachim Diebold
    • G06K9/00
    • G06T7/0012G06K9/0014G06T7/90G06T2207/30024
    • An analysis system automatically analyzes and counts fluorescence signals present in biopsy tissue marked using Fluorescence in situ Hybridization (FISH). The user of the system specifies classes of a class network and process steps of a process hierarchy. Then pixel values in image slices of biopsy tissue are acquired in three dimensions. A computer-implemented network structure is generated by linking pixel values to objects of a data network according to the class network and process hierarchy. Objects associated with pixel values at different depths of the biopsy tissue are used to determine the number, volume and distance between cell components. In one application, fluorescence signals that mark Her2/neural genes and centromeres of chromosome seventeen are counted to diagnose breast cancer. Her2/neural genes that overlap one another or that are covered by centromeres can be accurately counted. Signal artifacts that do not mark genes can be identified by their excessive volume.
    • 分析系统自动分析和计数使用荧光原位杂交(FISH)标记的活检组织中存在的荧光信号。 系统的用户指定类网络的类和进程层次结构的处理步骤。 然后在三维中获取活检组织的图像切片中的像素值。 通过根据类网络和进程层次将像素值链接到数据网络的对象来生成计算机实现的网络结构。 与活检组织不同深度处的像素值相关联的物体用于确定细胞组分之间的数量,体积和距离。 在一个应用中,计数标记Her2 /神经基因的荧光信号和17号染色​​体的着丝粒被诊断为乳腺癌。 可以准确计算Her2 /彼此重叠或被着丝粒覆盖的神经基因。 不标记基因的信号伪影可以通过其过量的体积来识别。